performance (0.3.0)

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Assessment of Regression Models Performance.

https://easystats.github.io/performance/
http://cran.r-project.org/web/packages/performance

Utilities for computing measures to assess model quality, which are not directly provided by R's 'base' or 'stats' packages. These include e.g. measures like r-squared, intraclass correlation coefficient (Nakagawa, Johnson & Schielzeth (2017) ), root mean squared error or functions to check models for overdispersion, singularity or zero-inflation and more. Functions apply to a large variety of regression models, including generalized linear models, mixed effects models and Bayesian models.

Maintainer: Daniel Luedecke
Author(s): Daniel Ldecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>)

License: GPL-3

Uses: bayestestR, insight, ICS, Matrix, betareg, lme4, nlme, pscl, psych, randomForest, survival, AER, mlogit, MASS, testthat, ordinal, lavaan, rmarkdown, brms, covr, loo, rstanarm, rstantools, ICSOutlier, glmmTMB, see
Reverse suggests: bayestestR

Released 2 months ago.


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